ObjectiveTo investigate the relation between disulfidptosis-related genes (DRGs) and prognosis or immunotherapy response of patients with pancreatic cancer (PC). MethodsThe transcriptome data, somatic mutation data, and corresponding clinical information of the patients with PC in The Cancer Genome Atlas (TCGA) were downloaded. The DRGs mutated in the PC were screened out from the 15 known DRGs. The DRGs subtypes were identified by consensus clustering algorithm, and then the relation between the identified DRGs subtypes and the prognosis of patients with PC, immune cell infiltration or functional enrichment pathway was analyzed. Further, a risk score was calculated according to the DRGs gene expression level, and the patients were categorized into high-risk and low-risk groups based on the mean value of the risk score. The risk score and overall survival of the patients with high-risk and low-risk were compared. Finally, the relation between the risk score and (or) tumor mutation burden (TMB) and the prognosis of patients with PC was assessed. ResultsThe transcriptome data and corresponding clinical information of the 177 patients with PC were downloaded from TCGA, including 161 patients with somatic mutation data. A total of 10 mutated DRGs were screened out. Two DRGs subtypes were identified, namely subtype A and subtype B. The overall survival of PC patients with subtype A was better than that of patients with subtype B (χ2=8.316, P=0.003). The abundance of immune cell infiltration in the PC patients with subtype A was higher and mainly enriched in the metabolic and conduction related pathways as compaired with the patients with subtype B. The mean risk score of 177 patients with PC was 1.921, including 157 cases in the high-risk group and 20 cases in the low-risk group. The risk score of patients with subtype B was higher than that of patients with subtype A (t=14.031, P<0.001). The overall survival of the low-risk group was better than that of the high-risk group (χ2=17.058, P<0.001), and the TMB value of the PC patients with high-risk was higher than that of the PC patients with low-risk (t=5.642, P=0.014). The mean TMB of 161 patients with somatic mutation data was 2.767, including 128 cases in the high-TMB group and 33 cases in the low-TMB group. The overall survival of patients in the high-TMB group was worse than that of patients in the low-TMB group (χ2=7.425, P=0.006). ConclusionDRGs are closely related to the prognosis and immunotherapy response of patients with PC, and targeted treatment of DRGs might potentially provide a new idea for the diagnosis and treatment of PC.
Objective To explore depression-related biomarkers and potential therapeutic drugs in order to alleviate depression symptoms and improve patients’ quality of life. Methods From November 2022 to January 2024, gene expression profiles of depression patients and healthy volunteers were downloaded from the Gene Expression Omnibus database. Differential expression analysis was performed to identify differentially expressed genes. Enrichment analysis of these genes was conducted, followed by the construction of a protein-protein interaction network. Finally, Cytoscape software with the Cytohubba plugin was used to identify potential key genes, and drug prediction was performed. Results Through differential expression analysis, a total of 110 differentially expressed genes (74 upregulated and 36 downregulated) were identified. Protein-protein interaction network identified 10 key genes, and differential expression analysis showed that 8 of these genes (CPA3, HDC, IL3RA, ENPP3, PTGDR2, VTN, SPP1, and SERPINE1) exhibited significant differences in expression levels between healthy volunteers and patients with depression (P<0.05). Enrichment analysis revealed that the upregulated genes were significantly enriched in pathways related to circadian rhythm, niacin and nicotinamide metabolism, and pyrimidine metabolism, while the downregulated genes were primarily enriched in extracellular matrix-receptor interaction and interleukin-17 signaling pathways. Six overlapping verification genes (SALL2, AKAP12, GCSAML, CPA3, FCRL3, and MS4A3) were obtained across two datasets using the Wayn diagram. Single-cell sequencing analysis indicated that these genes were significantly expressed in astrocytes and neurons. Mendelian randomization analysis suggested that the FCRL3 gene might play a critical role in the development of depression. Drug prediction analysis revealed several potential antidepressant agents, such as cefotiam, harmol, lincomycin, and ribavirin. Conclusions Circadian rhythm, nicotinate and nicotinamide metabolism, and pyrimidine metabolism pathways may represent potential pathogenic mechanisms in depression. Harmol may be a potential therapeutic drug for the treatment of depression.
ObjectiveAlthough evidence links idiopathic pulmonary fibrosis (IPF) and diabetes mellitus (DM), the exact underlying common mechanism of its occurrence is unclear. This study aims to explore further the molecular mechanism between these two diseases. MethodsThe microarray data of idiopathic pulmonary fibrosis and diabetes mellitus in the Gene Expression Omnibus (GEO) database were downloaded. Weighted Gene Co-Expression Network Analysis (WGCNA) was used to identify co-expression genes related to idiopathic pulmonary fibrosis and diabetes mellitus. Subsequently, differentially expressed genes (DEGs) analysis and three public databases were employed to analyze and screen the gene targets related to idiopathic pulmonary fibrosis and diabetes mellitus. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by Metascape. In addition, common microRNAs (miRNAs), common in idiopathic pulmonary fibrosis and diabetes mellitus, were obtained from the Human microRNA Disease Database (HMDD), and their target genes were predicted by miRTarbase. Finally, we constructed a common miRNAs-mRNAs network by using the overlapping genes of the target gene and the shared gene. ResultsThe results of common gene analysis suggested that remodeling of the extracellular matrix might be a key factor in the interconnection of DM and IPF. Finally, hub genes (MMP1, IL1R1, SPP1) were further screened. miRNA-gene network suggested that has-let-19a-3p may play a key role in the common molecular mechanism between IPF and DM. ConclusionsThis study provides new insights into the potential pathogenic mechanisms between idiopathic pulmonary fibrosis and diabetes mellitus. These common pathways and hub genes may provide new ideas for further experimental studies.
ObjectiveTo explore the mechanism of DDX46 regulation of esophageal squamous cell carcinoma.MethodsPicture signals of fluorescence in gene array were scanned and differential expression of gene in two groups (a DDX46-shRNA-LV group and a control-LV group) were compared by GCOSvL.4 software. These differential expressed genes were analyzed by bioinformatics methods finally, and validated by quantitative real time polymerase chain reaction (qRT-PCR) analysis.ResultsAccording to the screening criteria of fold change ≥2 and P<0.05, 1 006 genes were differentially expressed after DDX46 knockdown, including 362 up-regulated and 644 down-regulated genes. Bioinformatics analysis and gene co-expression network building identified that these differentially expressed genes were mainly involved in cell cycle, proliferation, apoptosis, adhesion, energy metabolism, immune response, etc. Phosphatidylinositol 3-kinase (PI3K) was the key molecule in the network. The results of RT-qPCR were completely consistent with the results of gene microarra.ConclusionBioinformatics can effectively exploit the microarray data of esophageal squamous cell carcinoma after DDX46 knockdown, which provides a valuable clue for further exploration of DDX46 tumorigenesis mechanism and helps to find potential drug therapy.
Objective To explore key genes and mechanisms of depression aggravating Crohn disease. Methods In March 2023, the Public Health Genomics and Precision Health Knowledge Base and Gene Expression Omnibus database were used to identify the overlapping differentially expressed genes between Crohn disease and depression and the key genes were screened by Metascape, STRING, Cytoscape, and protein interaction network analysis. The Gene Expression Omnibus database was used to analyze the correlations between key genes and clinical pathologies such as Crohn Disease Endoscopic Index of Severity and intestinal microvilli length. Results There were 137 overlapping differentially expressed genes between Crohn disease and depression, and 25 key genes were further screened out. Among them, CREB1, FKBP5, MAPT, NTSR1, OXTR, PROK2, POMC, HTR2B, and PPARGC1A genes were significantly correlated with multiple clinical parameters. The functions of PROK2 and PROK2-related genes were mainly enriched in neutrophil and granulocyte migration, neutrophil and granulocyte chemotaxis, etc. Conclusions There are 25 key genes, especially CREB1, FKBP5, MAPT, NTSR1, OXTR, PROK2, POMC, HTR2B, and PPARGC1A, that possibly contribute to the establishment and deterioration of Crohn disease caused by depressive disorder. Among these genes, PROK2 showes the possibility of regulating immune cell (neutrophils and CD8+ T cells) infiltration.
ObjectiveTo analyze the expression and clinical significance of cyclin-dependent kinase 1 (CDK1) in lung adenocarcinoma by bioinformatics.MethodsBased on the gene expression data of lung adenocarcinoma patients in The Cancer Genome Atlas (TCGA), the differential expression of CDK1 in lung adenocarcinoma tissues and normal lung tissues was analyzed. The expression of CDK1 gene in lung adenocarcinoma was analyzed by UALCAN at different angles. Survival analysis of different levels of CDK1 gene expression in lung adenocarcinoma was performed using Kaplan-Meier Plotter. Correlation Cox analysis of CDK1 expression and overall survival was based on clinical data of lung adenocarcinoma in TCGA. Gene set enrichment analysis was performed on gene sequences related to CDK1 expression in clinical cases. The protein interaction network of CDK1 from Homo sapiens was obtained by STRING. CDK1-related gene proteins were obtained and analyzed by the web server Gene Expression Profiling Interactive Analysis (GEPIA).ResultsBased on the analysis of TCGA gene expression data, CDK1 expression in lung adenocarcinoma was higher than that in normal lung tissues. UALCAN analysis showed that high CDK1 expression may be associated with smoking. Survival analysis indicated that when CDK1 gene was highly expressed, patients with lung adenocarcinoma had a poor prognosis. Univariate and multivariate Cox regression analysis of CDK1 expression and overall survival showed that high CDK1 expression was an independent risk factor for survival of patients with lung adenocarcinoma. Gene set enrichment analysis revealed that high CDK1 expression was closely related to DNA replication, cell cycle, cancer pathway and p53 signaling pathway.ConclusionCDK1 may be a potential molecular marker for prognosis of lung adenocarcinoma. In addition, CDK1 regulation may play an important role in DNA replication, cell cycle, cancer pathway and p53 signaling pathway in lung adenocarcinoma.
The purpose of this paper is to present the research on the molecular biological characteristics of proto-oncogene pim-2 and to analyze the related mechanism. Proto-oncogene pim-2 was studied and analyzed by the bioinformatics method and technology. With an online server, the chromosomal localization of pim-2 gene was analyzed, and the exon, open reading frame, CpG island and miRNAs complementary fragments and the like were predicted. With bioinformatics software, the physicochemical property of transcription protein of proto-oncogene pim-2 and various modification sites of protein sequence, such as ubiquitination and glycosylation, were predicted, the antigenic index was calculated, and the spatial structural was modeled. The research findings showed that the proto-oncogene pim-2 comprised six exons, the CDS (coding sequence) transcribed a section of peptide chain including 311 amino acids, a gene promoter has a CpG island, and the 3'UTR region contains an miRNA gene. The molecular weight of the Pim-2 protein was 34, 188.47, the isoelectric point was 5.78, the instability index was 45.87, and the extinction coefficient was 279nm. A plurality of covalent modification sites, two ubiquitination sites, four glycosylation sites, an SUMO sumoylation site, a nitrosation site, two palmitoylation sites and sixteen regions with higher antigenic index were distributed in the protein sequence. This research showed that the related regions and modification sites distributed on the sequence of proto-oncogene pim-2 were closely related to the carcinogenic effect thereof.
ObjectiveTo analyze the expression of cold-induced RNA-binding protein (CIRBP) in lung adenocarcinoma and its clinical significance based on bioinformatics, in order to provide a new direction for the study of therapeutic targets for lung adenocarcinoma.MethodsThe CIRBP gene expression data and patient clinical information data in lung adenocarcinoma tissues and adjacent tissues were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. The expression of CIRBP in lung adenocarcinoma was analyzed. Furthermore, its relationship with clinicopathological features and prognosis in patients with lung adenocarcinoma was analyzed. GO and KEGG enrichment analysis were carried out for the screened genes. The CIRBP protein interaction network was constructed by STRING, and the correlation analysis was carried out using the GEPIA online website.ResultsThe expression level of CIRBP gene in lung adenocarcinoma tissues was significantly lower than that in adjacent tissues (P<0.01), and its expression level was correlated with T stage and N stage in clinicopathological features. The prognosis of patients with high CIRBP expression in lung adenocarcinoma was significantly better than that with low CIRBP expression. Univariate and multivariate Cox regression analysis showed that CIRBP was an independent prognostic factor in patients with lung adenocarcinoma. GO functional annotation showed its enrichment in organelle fission, nuclear fission, chromosome separation, and DNA replication, etc. KEGG analysis showed that it was mainly involved in cell cycle and DNA replication. Protein interaction network and GEPIA online analysis showed that the expression level of CIRBP was negatively correlated with the expression level of cyclin B2.ConclusionCIRBP gene is down-regulated in lung adenocarcinoma tissues, and its expression level is closely related to patient prognosis. CIRBP gene may be a potential therapeutic target and prognostic marker for lung adenocarcinoma.
Objective To identify potential hub genes and key pathways in the early period of septic shock via bioinformatics analysis. MethodsThe gene expression profile GSE110487 dataset was downloaded from the Gene Expression Omnibus database. Differentially expressed genes were identified by using DESeq2 package of R project. Then Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were constructed to investigated pathways and biological processes using clusterProfiler package. Subsequently, protein-protein interaction (PPI) network was mapped using ggnetwork package and the molecular complex detection (MCODE) analysis was implemented to further investigate the interactions of differentially expressed genes using Cytoscape software. Results A total of 468 differentially expressed genes were identified in septic shock patients with different responses who accepted early supportive hemodynamic therapy, including 255 upregulated genes and 213 downregulated genes. The results of GO and the KEGG pathway enrichment analysis indicated that these up-regulated genes were highly associated with the immune-related biological processes, and the down-regulated genes are involved in biological processes related to organonitrogen compound, multicellular organismal process, ion transport. Finally, a total of 23 hub genes were identified based on PPI and the subcluster analysis through MCODE software plugin in Cytoscape, which included 19 upregulated hub genes, such as CD28, CD3D, CD8B, CD8A, CD160, CXCR6, CCR3, CCR8, CCR9, TLR3, EOMES, GZMB, PTGDR2, CXCL8, GZMA, FASLG, GPR18, PRF1, IDO1, and additional 4 downregulated hub genes, such as CNR1, GPER1, TMIGD3, GRM2. KEGG pathway enrichment analysis and GO functional annotation showed that differentially expressed genes were primarily associated with the items related to cytokine-cytokine receptor interaction, natural killer cell mediated cytotoxicity, hematopoietic cell lineage, T cell receptor signaling pathway, phospholipase D signaling pathway, cell adhesion molecules, viral protein interaction with cytokine and cytokine receptor, primary immunodeficiency, graft-versus-host disease, type 1 diabetes mellitus. Conclusions Some lymphocytes such as T cells and natural killer cells, cytokines and chemokines participate in the immune process, which plays an important role in the early treatment of septic shock, and CD160, CNR1, GPER1, and GRM2 may be considered as new biomarkers.
ObjectiveTo explore the clinical significance and possible potential mechanism of hepatocellular carcinoma through the screening of key genes in hepatocellular carcinoma.MethodsHepatocellular carcinoma gene chip was obtained from GEO database, differentially expressed genes (DEGs) were screened by GEO2R online tools and Venn map, GO analysis and KEGG pathway analysis were performed in DAVID database, core genes were screened by STRING and Cytscape software, core genes were analyzed in Kaplan-Meier Plotter for survival analysis, and expression was analyzed by GEPIA database. The core genes related to prognosis and highly expressed in hepatocellular carcinoma were analyzed by Metascape online tool for function and pathway enrichment analysis. Finally, the key genes were verified in hepatocellular carcinoma and paracancerous tissues.ResultsA total of 94 DEGs were screened from three gene chips GSE14520, GSE60502, and GSE102079, obtained from GEO. After the selected DEGs was analyzed by GO function analysis, KEGG pathway enrichment analysis, STRING and Cytscape software by DAVID, 19 core DEGs were screened. After 19 core DEGs were analyzed by Kaplan-Meier Plotter website, 9 genes [ribonucleotide reductase M2 (RRM2), polycomb repressive complex 1 (PRC1), topoisomerase Ⅱ alpha (TOP2A), aurora kinase A (AURKA), nucleolar spindle-associated protein 1 (NUSAP1), Rac-GTPase activating protein 1 (RACGAP1), abnormal spindle-like microcephaly-associated (ASPM), cyclin dependent kinase 1 (CDK1) and GINS complex subunit 1 (GINS1)] were found to be associated with the prognosis of hepatocellular carcinoma. The expressions of these 9 genes were analyzed by GEPIA, and the results showed that all 9 genes were highly expressed in hepatocellular carcinoma tissues. The functions and pathways of 9 highly expressed genes were analyzed by metascape website. Finally, RRM2 was selected for verification in hepatocellular carcinoma tissues and adjacent tissues, and it was found that the staining score of RRM2 in hepatocellular carcinoma tissues was (10.9±1.5) points, which was significantly higher than its staining score in adjacent tissues [(4.5±1.2) points], P<0.001.ConclusionThe nine genes identified by bioinformatics analysis may be the key genes in the occurrence and development of hepatocellular carcinoma, which can provide reference for further study on the pathogenesis, diagnosis and treatment of hepatocellular carcinoma.
